Knowledge graphs are powerful tools for linking complex information, yet they remain underused in archaeology and paleontology. StratiGraph makes them practical and accessible, enabling researchers to connect data from fieldwork, laboratory analysis, archives, and bibliographic sources within a unified semantic framework.

Using real-time AI checks against controlled vocabularies, instant 3D replication for spatial annotation, and semantic linking of photographs, this method produces clean, ready-to-publish data without the burden of post-processing.

This approach allows researchers to work efficiently in the field, even without internet, while synchronizing automatically when online. By processing routine tasks locally and reserving cloud resources for collaboration, StratiGraph reduces server load, minimizes data transfer, and lowers the carbon footprint.

StratiGraph enables real-time suggestions of relevant comparative materials, similar contexts, and key references during documentation, while also digitizing and semantically enriching archival resources to make them machine-readable.

Knowledge graphs are powerful tools for linking complex information, yet they remain underused in archaeology and paleontology. StratiGraph makes them practical and accessible, enabling researchers to connect data from fieldwork, laboratory analysis, archives, and bibliographic sources within a unified semantic framework.

Using real-time AI checks against controlled vocabularies, instant 3D replication for spatial annotation, and semantic linking of photographs, this method produces clean, ready-to-publish data without the burden of post-processing.

This approach allows researchers to work efficiently in the field, even without internet, while synchronizing automatically when online. By processing routine tasks locally and reserving cloud resources for collaboration, StratiGraph reduces server load, minimizes data transfer, and lowers the carbon footprint.

StratiGraph enables real-time suggestions of relevant comparative materials, similar contexts, and key references during documentation, while also digitizing and semantically enriching archival resources to make them machine-readable.

Knowledge graphs are powerful tools for linking complex information, yet they remain underused in archaeology and paleontology. StratiGraph makes them practical and accessible, enabling researchers to connect data from fieldwork, laboratory analysis, archives, and bibliographic sources within a unified semantic framework.

Using real-time AI checks against controlled vocabularies, instant 3D replication for spatial annotation, and semantic linking of photographs, this method produces clean, ready-to-publish data without the burden of post-processing.

This approach allows researchers to work efficiently in the field, even without internet, while synchronizing automatically when online. By processing routine tasks locally and reserving cloud resources for collaboration, StratiGraph reduces server load, minimizes data transfer, and lowers the carbon footprint.

StratiGraph enables real-time suggestions of relevant comparative materials, similar contexts, and key references during documentation, while also digitizing and semantically enriching archival resources to make them machine-readable.